= Partitioned Job
An example of the usage of the `DeployerPartitionHandler` and
`DeployerStepExecutionHandler` to partition a Spring Batch job.
== Requirements:
* Java 17 or Above
== Build:
[source,shell]
----
./mvnw clean install
----
== Execute:
[source,shell]
----
export SPRING_APPLICATION_JSON='{"spring.datasource.url":"jdbc:mariadb://localhost:3306/<your database>","spring.datasource.password":"<your password>","spring.datasource.username":"<your username>","spring.datasource.driverClassName":"org.mariadb.jdbc.Driver"}'
java -jar target/partitioned-batch-job-3.0.0.jar
----
NOTE: This example will use require a MySql RDBMS repository and currently uses the mariadb jdbc driver to connect.
You can changes this another driver based on your needs.
NOTE: Since this example uses the Spring Cloud Deployer Local to launch the partitions, you will need to establish the datasource settings using the SPRING_APPLICATION_JSON environment property as shown above.
== Dependencies:
A datasource (not in memory) must be configured based on normal Spring Boot conventions
(application.properties, application.yml, environment variables).
== Asynchronous remote partition task launch
Currently partitions are launched sequentially. To launch them asynchronously set the following environment variables:
* `spring.cloud.task.closecontextEnabled=true`
* `io.spring.asynchronous=true`
NOTE: We need to close the context since the use of ThreadPoolTaskExecutor leaves a thread active thus the app will not terminate.
To close the application appropriately, we will need to set `spring.cloud.task.closecontextEnabled`` to true.
2ef93291fc